Pruning Boolean Expressions to Shorten Dynamic Slices

This paper presents a novel extension to dynamic slicing that we call pruned slicing. The proposed slicing approach produces smaller slices than traditional dynamic slicing. This is achieved by reasoning over Boolean expressions. We have implemented a prototype in Python and empirically evaluated its performance on three different benchmarks: TCAS, QuixBugs and the Refactory dataset. We show that pruned slicing reduces the size of dynamic slices on average by 10.96 percent for TCAS. For QuixBugs and the Refactory dataset, the slice size remains the same, but the number of Boolean expressions within the slice is reduced. Further, the empirical evaluation shows that pruned dynamic slicing comes with a low computational overhead compared to dynamic slicing. Pruned slicing can also be used in combination with relevant slicing.